> Markdown version of [/jobs/ext/3364278-senior-forward-deployed-engineer-generative-ai-google-cloud-munich-berlin-frankfurt-or-hamburg](https://www.wearedevelopers.com/jobs/ext/3364278-senior-forward-deployed-engineer-generative-ai-google-cloud-munich-berlin-frankfurt-or-hamburg). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Forward Deployed Engineer, Generative AI, Google Cloud - Munich, Berlin, Frankfurt or Hamburg

- **Company:** Google
- **Location:** Berlin, Germany
- **Experience:** Expert
- **Salary:** €128,000.0 - €131,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Python (Programming Language), Rapid Prototyping Process, Software Engineering, Unstructured Data, Google Cloud, ReactJS, Large Language Models, Multi-Agent Systems, Generative AI, Information Technology, Data Pipelines, Programming Languages
- **Published:** September 8, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=98f257196121179f

## About the Role

* Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
 * 5 years of experience with software development using Python or similar coding languages.
 * Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., GCP).
 * Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
 * Experience leading technical discovery sessions., * Master's or PhD in AI, Computer Science, or a related technical field.
 * Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
 * Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

## Description

* Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
 * Architect and code the "connective tissue" between Google's AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
 * Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
 * Identify repeatable field patterns and friction points in Google's AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
 * Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.